Method of applying edge offset

ABSTRACT

Provided is a method of post-processing a reconstructed image. The method according to an embodiment includes determining a boundary strength for each 4-sample edge which is a prediction edge or a transform edge and lies on 8×8 sample grid, determining whether deblocking filtering is applied on the 4-sample edge or not using the boundary strength and a boundary quantization parameter, filtering the 4-sample edge if the deblocking filtering is applied on the 4-sample edge, and applying an edge offset if a sample adaptive offset (SAO) type indicates an edge offset.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a Continuation of copending U.S. application Ser.No. 14/349,451, filed on Apr. 3, 2014, which is the National Phase ofPCT International Application No. PCT/CN2013/070222 on Jan. 8, 2013,which claims the benefit under under 35 U.S.C. §119(a) to PatentApplication No. 10-2012-0005334, filed in Korea on Jan. 17, 2012, all ofwhich are hereby expressly incorporated by reference into the presentapplication.

BACKGROUND OF THE INVENTION

1. Technical Field

The present invention relates to a sample adaptive offset method forreducing difference between original samples and reconstructed samples,and more particularly, to a method of adaptively adding an offset toreconstructed samples based on the difference between a current sampleand neighboring samples.

2. Discussion of the Related Art

For compression of video data, a plurality of video standards has beendeveloped. Such video standards are, for example, MPEG-2, MPEG-4 andH.264/MPEG-4 AVC. As a successor to H.264/MPEG-4 AVC, High EfficiencyVideo Coding (HEVC) is currently under joint development by the ISO/IECMoving Picture Experts Group (MPEG) and ITU-T Video Coding Expert Group(VCEG).

According to HEVC, one picture is divided into largest coding units(LCUs), one or more coding units of each LCU are encoded by generating aprediction block using inter prediction or intra prediction. Thedifference between an original block and the prediction block istransformed to generate a transformed block, and the transformed blockis quantized using a quantization parameter and one of a plurality ofpredetermined quantization matrices. The quantized coefficients of thequantized block are scanned by a predetermined scan type and thenentropy-coded. The quantized coefficients are inversely quantized andinversely transformed to generate a residual block which is combinedwith the prediction block to generate reconstructed image. Thereconstructed image is adaptively filtered using one or more deblockingfilter to remove blocking artifacts.

But, the technique of deblocking filter described in H.264 and HEVCunder development deteriorates decoding performance of a decodingapparatus because the technique is too complicated. Also, even if thedeblocking filtering is applied to the block edges, the differencesbetween the original samples and the filtered samples are stillremained. To compensate the differences, sample adaptive offset (SAO)process is introduced. But, according to the current SAO process, thedifferences between the original samples and the filtered samplesincrease occasionally because the optimum edge index should not bedetermined.

Therefore, new technique is required to reduce the complexity of thepost-processing and to improve the performance of the post-processing.

SUMMARY OF THE INVENTION

The present invention is directed to a method of an edge offset toreduce the difference between original samples and reconstructed samplesand to reduce the quantity of bits required for compensating thedifferences.

One aspect of the present invention provides a method of applying anedge offset, comprising: generating an edge index of a current sample,and applying an edge offset corresponding to the edge index to thecurrent sample. The edge index is generated using the differencesbetween a current sample and two neighboring samples determined by anedge offset type.

A method according to the present invention generates an edge index of acurrent sample, and applies an edge offset corresponding to the edgeindex to the current sample. The edge index is generated using thedifferences between a current sample and two neighboring samplesdetermined by an edge offset type. Accordingly, the difference betweenoriginal samples and reconstructed samples are effectively reduced bygenerating the optimum edge index. Also, the quantity of bits requiredfor reducing the differences are reduced by fixing the sign of offset topositive or negative.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram illustrating a moving picture encodingapparatus according to an embodiment of the present invention.

FIG. 2 is a block diagram illustrating a moving picture decodingapparatus according to an embodiment of the present invention.

FIG. 3 is a flow chart illustrating a deblocking filtering processaccording to an embodiment of the present invention.

FIG. 4 is a conceptual diagram illustrating a method of determining theboundary strength according to an embodiment of the present invention.

FIG. 5 is a conceptual diagram illustrating a 4-sample edge according toan embodiment of the present invention.

FIG. 6 is a conceptual diagram illustrating a method of dividing apicture into multiples areas according to an embodiment of the presentinvention.

FIG. 7 is a conceptual diagram illustrating edge types according to anembodiment of the present invention.

FIG. 8 is a conceptual diagram illustrating edge indexes according to anembodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

Hereinafter, various embodiments of the present invention will bedescribed in detail with reference to the accompanying drawings.However, the present invention is not limited to the exemplaryembodiments disclosed below, but can be implemented in various types.Therefore, many other modifications and variations of the presentinvention are possible, and it is to be understood that within the scopeof the disclosed concept, the present invention may be practicedotherwise than as has been specifically described.

A moving picture encoding apparatus and an moving picture decodingapparatus according to the present invention may be a user terminal suchas a personal computer, a personal mobile terminal, a mobile multimediaplayer, a smartphone or a wireless communication terminal. The imageencoding device and the image decoding device may be include acommunication unit for communicating with various devices, a memory forstoring various programs and data used to encode or decode images.

FIG. 1 is a block diagram illustrating a moving picture encodingapparatus 1000 according to the present invention.

Referring to FIG. 1, the moving picture encoding apparatus 1000 includesa picture division unit 1010, a transform unit 1020, a quantization unit1030, a scanning unit 1040, an entropy coding unit 1050, an intraprediction unit 1060, an inter prediction unit 1070, an inversequantization unit 1080, an inverse transform unit 1090, apost-processing unit 1100, a picture storing unit 1110, a subtractionunit 1120 and an addition unit 1130.

The picture division unit 1010 divides a picture or a slice into plurallargest coding units (LCUs), and divides each LCU into one or morecoding units. The size of LCU may be 32×32, 64×64 or 128×128. Thepicture division unit 1010 determines prediction mode and partitioningmode of each coding unit.

An LCU includes one or more coding units. The LCU has a recursive quadtree structure to specify a division structure of the LCU. Parametersfor specifying the maximum size and the minimum size of the coding unitare included in a sequence parameter set. The division structure isspecified by one or more split coding unit flags. The size of a codingunit is 2N×2N. If the size of the LCU is 64×64 and the size of asmallest coding unit (SCU) is 8×8, the size of the coding unit may be64×64, 32×32, 16×16 or 8×8.

A coding unit includes one or more prediction units. In intraprediction, the size of the prediction unit is 2N×2N or N×N. In interprediction, the size of the prediction unit is specified by thepartitioning mode. The partitioning mode is one of 2N×2N, 2N×N, N×2N andN×N if the coding unit is partitioned symmetrically. The partitioningmode is one of 2N×nU, 2N×nD, nL×2N and nR×2N if the coding unit ispartitioned asymmetrically.

A coding unit includes one or more transform units. The transform unithas a recursive quad tree structure to specify a division structure ofthe coding unit. The division structure is specified by one or moresplit transform unit flags. Parameters for specifying the maximum sizeand the minimum size of the transform unit are included in a sequenceparameter set.

The transform unit 1020 transforms residual signals to generate atransformed block. The residual signals are transformed in a transformunit basis. The residual signals are derived by subtracting a predictionblock which is generated by the intra prediction unit 1060 or the interprediction unit 1070 from an original block.

Different transform matrix may be used according to the prediction mode(intra prediction mode or inter prediction mode). Also, in intraprediction mode, the transform matrix may be adaptively determined basedon an intra prediction mode. The transform unit is transformed using two1-dimentional transform matrixes (horizontal matrix and verticalmatrix). For example, in horizontal intra prediction mode of intraprediction, a DCT-based integer matrix is applied to vertical directionand a DST-based or KLT-based integer matrix is applied to horizontaldirection because the residual signals may have vertical directionality.In vertical intra prediction mode of intra prediction, a DCT-basedinteger matrix is applied to horizontal direction and a DST-based orKLT-based integer matrix is applied to vertical direction.Alternatively, the kind of transform matrix is determined based on thesize of the transform unit.

The quantization unit 1030 determines a quantization parameter forquantizing the transformed block. The quantization parameter is aquantization step size. The quantization parameter is determined per aquantization unit. The quantization unit is a coding unit larger than orequal to a predetermined size. The predetermined size is called aminimum size of the quantization unit. The quantization unit having theminimum size is called a minimum quantization unit. If a size of thecoding unit is equal to or larger than a minimum size of thequantization unit, the coding unit becomes the quantization unit. Aplurality of coding units may be included in the minimum quantizationunit. The minimum quantization unit may be an 8×8 block or a 16×16block. The minimum size may be is determined per picture.

The quantization unit 1030 generates a quantization parameter predictorand generates a differential quantization parameter by subtracting thequantization parameter predictor from the quantization parameter. Thedifferential quantization parameter is entropy-coded.

The quantization parameter predictor is generated as follows.

First Embodiment

The quantization parameters of a left coding unit, an above coding unitand an above-left coding unit are sequentially retrieved in this order.The quantization parameter predictor is generated using one or twoavailable quantization parameters. For example, the first availablequantization parameter is set as the quantization parameter predictor.Or an average of first two available quantization parameters is set asthe quantization parameter predictor, and if only one quantizationparameter is available, the available quantization parameter is set asthe quantization parameter predictor.

Second Embodiment

There may be none of a left coding unit, an above coding unit and anabove left coding unit of the current coding unit. On the other hand,there may be a previous coding unit of the current coding unit in codingorder. Thus, the quantization parameters of neighboring coding unitsadjacent to the current coding unit and the previous coding unit may beused to generate the quantization parameter predictor. The quantizationparameters are retrieved as the following order; 1) the quantizationparameter of a left neighboring coding unit, 2) the quantizationparameter of an above neighboring coding unit, 3) the quantizationparameter of an above-left neighboring coding unit, and 4) thequantization parameter of the previous coding unit.

Alternatively, the quantization parameters are retrieved as thefollowing order; 1) the quantization parameter of a left neighboringcoding unit, 2) the quantization parameter of an above neighboringcoding unit, and 3) the quantization parameter of the previous codingunit.

An average of first two available quantization parameters is set as thequantization parameter predictor when two or more quantizationparameters are available, and when only one quantization parameter isavailable, the available quantization parameter is set as thequantization parameter predictor. For example, if the quantizationparameters of the left and above coding units are available, an averageof the left and above quantization parameters is set as the quantizationparameter predictor. If only one of the quantization parameters of theleft and above coding units is available, an average of the availablequantization parameter and the quantization parameter of the previouscoding unit is set as the quantization parameter predictor. If thequantization parameters of the left and above coding units areunavailable, the quantization parameter of the previous coding unit isset as the quantization parameter predictor. The average is rounded off.

The quantization unit 1030 quantizes the transformed block using aquantization matrix and the quantization parameter to generate aquantized block. The quantized block is provided to the inversequantization unit 1080 and the scanning unit 1040.

The scanning unit 1040 scans the quantized coefficients and transformsthe quantized coefficients into 1-dimentional quantized coefficientcomponents applying a scan pattern to the quantized block.

In intra prediction mode, the distribution of the quantized coefficientsvaries according to the intra prediction mode and the size of thetransform unit. Thus, the scan pattern is determined based on the intraprediction mode and the size of the transform unit. The scan pattern maybe selected among a zigzag scan, vertical scan and horizontal scan. Thezigzag scan may be replaced with a diagonal scan.

For example, if the size of the transform unit is equal to or smallerthan 8×8, the horizontal scan is selected for the vertical mode and apredetermined number of neighboring intra prediction modes of thevertical mode, the vertical scan is selected for the horizontal mode andthe predetermined number of neighboring intra prediction modes of thehorizontal mode, and the zigzag scan or the diagonal scan is selectedfor the other intra prediction modes. When the size of the transformunit is larger than 8×8, the zigzag scan or the diagonal scan isselected for all intra prediction modes.

In inter prediction mode, a predetermined scan pattern is used. Thepredetermined scan pattern may be a zigzag scan or a diagonal scan.

When the size of the transform unit is larger than a predetermined size,the quantized coefficients are divided into a plurality of subsets andthen scanned. The predetermined size may be 4×4. The scan pattern forscanning the subsets is the same as the scan pattern for scanningquantized coefficients within each subset. The quantized coefficientswithin each subset are scanned in the reverse direction. The subsets arealso scanned in the reverse direction.

A parameter indicating a last non-zero position is encoded andtransmitted to the decoder. The last non-zero position specifiesposition of last non-zero quantized coefficient within the transformunit. A parameter indicating a position of a last non-zero quantizedcoefficient within each subset is also transmitted to the decodingapparatus.

The inverse quantization unit 1080 inversely quantizes the quantizedcoefficients. The inverse transform unit 1090 inversely transforms theinverse-quantized coefficients to generate residual signals.

The addition unit 1130 adds the residual signals generated by theinverse transform unit 1090 and prediction signals generated by theintra prediction unit 1060 or the inter prediction unit 1070. Thesubtraction unit 1120 subtracts prediction samples from original samplesto generate residual signals.

The post-processing unit 1100 performs deblocking filtering process, asample adaptive offset process, and an adaptive loop filtering process.

The deblocking filtering process is performed to remove blockingartifacts which appears in the reconstructed picture.

The sample adaptive offset process is performed after performing thedeblocking filtering process to reduce difference between an originalsample and a reconstructed sample. It is determined per picture or slicewhether the sample adaptive offset process is performed or not. Thepicture or the slice may be divided into a plurality of offset areas,and an offset type may be determined per each area. There are four edgeoffset types and two band offset types. If the offset type is one of theedge offset types, an edge type is determined per each sample within theoffset area, and an offset corresponding to the edge type is added tothe each sample. The edge type is determined by comparing the currentsample with neighboring two samples.

The adaptive loop filtering process may be performed by comparing thereconstructed image and an original image to obtain filter coefficients.The filter coefficients are applied all samples within 4×4 block or 8×8block. Whether the adaptive loop filtering is performed or not isdetermined per coding unit. Therefore, the size and coefficients of theloop filter may be changed on a coding unit basis.

The picture storing unit 1110 receives reconstructed pictures from thepost-processing unit 1100 and stores them in a memory. The picture is aframe-based picture or a field-based picture.

The inter prediction unit 1070 performs motion estimation using one ormore pictures stored in the picture storing unit 1110, and determinesone or more reference picture indexes specifying one or more referencepictures and one or more motion vectors. The inter prediction unit 1070generates a prediction block using the one or more reference pictureindexes and the one or more motion vectors.

The intra prediction unit 1060 determines an intra prediction mode of acurrent prediction unit and generates a prediction block using the intraprediction mode.

The entropy coding unit 1050 entropy-codes the quantized coefficientcomponents received from the scanning unit 1040, intra predictioninfoitnation received from the intra prediction unit 1060, motioninformation received from the inter prediction unit 1070.

FIG. 2 is a block diagram illustrating a moving picture decodingapparatus 2000 according to the present invention.

As shown in FIG. 2, the moving picture decoding apparatus 2000 includesan entropy decoding unit 2010, an inverse scanning unit 2020, an inversequantization unit 2030, an inverse transform unit 2040, an intraprediction unit 2050, an inter prediction unit 2060, a post-processingunit 2070, a picture storing unit 2080 and an addition unit 2090.

The entropy decoding unit 2010 extracts and entropy-decodes the intraprediction information, the inter prediction information and thequantized coefficient components from a received bit stream. The entropydecoding unit 2010 transmits the inter prediction information to theinter prediction unit 2060, transmits the intra prediction informationto the intra prediction unit 2050, and transmits the quantizedcoefficient components to the inverse scanning unit 2020.

The inverse scanning unit 2020 transforms the quantized coefficientcomponents into 2-dimential quantized block using an inverse scanpattern.

In intra prediction mode, the inverse scan pattern is selected based onthe intra prediction mode and the size of the transform unit. Theinverse scan pattern may be selected among a zigzag scan, vertical scanand horizontal scan. The zigzag scan may be replaced with a diagonalscan.

For example, if the size of the transform unit is equal to or smallerthan 8×8, the horizontal scan is selected for the vertical mode and apredetermined number of neighboring intra prediction modes of thevertical mode, the vertical scan is selected for the horizontal mode andthe predetermined number of neighboring intra prediction modes of thehorizontal mode, and the zigzag scan or the diagonal scan is selectedfor the other intra prediction modes. When the size of the transformunit is larger than 8×8, the zigzag scan or the diagonal scan isselected for all intra prediction modes.

In inter prediction mode, a predetermined scan pattern is used. Thepredetermined scan pattern may be a zigzag scan or a diagonal scan.

If the size of the current transform unit is larger than a predeterminedsize, the quantized coefficient components are inversely scanned in asubset basis to construct the quantized block. The subset has thepredetermined size. The predetermined size may be 4×4. If the size ofthe transform unit is equal to the predetermined size, the quantizedcoefficient components of the transform unit are inversely scanned toconstruct the transform unit. When the quantized coefficient componentsare inversely scanned in a subset basis, the same inverse scanningpattern is applied to the quantized coefficient components of eachsubset.

The multiple subsets are inversely scanned in reverse direction. Thequantized coefficient components are also inversely scanned in reversedirection. The inverse scan pattern applied to the quantized coefficientcomponents to construct a subset is the same as the inverse scan patternapplied to the multiple constructed subsets. The inverse scanning unit2020 performs inverse scanning using the parameter indicating a positionof a last non-zero quantized coefficient of the transform unit.

The inverse quantization unit 2030 receives the differentialquantization parameter from the entropy decoding unit 2010 and generatesa quantization parameter predictor to obtain a quantization parameter ofa current coding unit.

The quantization parameter predictor is generated as follows

First Embodiment

The quantization parameters of a left coding unit, an above coding unitand an above-left coding unit are sequentially retrieved in this order.The quantization parameter predictor is generated using one or twoavailable quantization parameters. For example, the first availablequantization parameter is set as the quantization parameter predictor.Or an average of first two available quantization parameters is set asthe quantization parameter predictor, and if only one quantizationparameter is available, the available quantization parameter is set asthe quantization parameter predictor.

Second Embodiment

There may be none of a left coding unit, an above coding unit and anabove left coding unit of the current coding unit. On the other hand,there may be a previous coding unit of the current coding unit in codingorder. Thus, the quantization parameters of neighboring coding unitsadjacent to the current coding unit and the previous coding unit may beused to generate the quantization parameter predictor. The quantizationparameters are retrieved as the following order; 1) the quantizationparameter of a left neighboring coding unit, 2) the quantizationparameter of an above neighboring coding unit, 3) the quantizationparameter of an above-left neighboring coding unit, and 4) thequantization parameter of the previous coding unit.

Alternatively, the quantization parameters are retrieved as thefollowing order; 1) the quantization parameter of a left neighboringcoding unit, 2) the quantization parameter of an above neighboringcoding unit, and 3) the quantization parameter of the previous codingunit.

An average of first two available quantization parameters is set as thequantization parameter predictor when two or more quantizationparameters are available, and when only one quantization parameter isavailable, the available quantization parameter is set as thequantization parameter predictor. For example, if the quantizationparameters of the left and above coding units are available, an averageof the left and above quantization parameters is set as the quantizationparameter predictor. If only one of the quantization parameters of theleft and above coding units is available, an average of the availablequantization parameter and the quantization parameter of the previouscoding unit is set as the quantization parameter predictor. If thequantization parameters of the left and above coding units areunavailable, the quantization parameter of the previous coding unit isset as the quantization parameter predictor. The average is rounded off.

The inverse quantization unit 2030 generates the quantization parameterof the current coding unit by adding the differential quantizationparameter and the quantization parameter predictor. If the differentialquantization parameter for the current coding unit is not transmittedfrom an encoding side, the differential quantization parameter is set tozero. The quantization parameter is generated per quantization unit.

The inverse quantization unit 2030 inversely quantizes the quantizedblock.

The inverse transform unit 2040 inversely transforms theinverse-quantized block to generate a residual block. The inversetransform matrix type is determined based on the prediction mode (intraprediction mode or inter prediction mode) and the size of the transformunit.

The addition unit 2090 generates reconstructed samples by adding theresidual block and a prediction block.

The intra prediction unit 2050 recovers the intra prediction mode of thecurrent prediction unit based on the intra prediction informationreceived from the entropy decoding unit 2010, and generates a predictionblock according to the intra prediction mode.

The inter prediction unit 2060 recovers one or more reference pictureindexes and one or more motion vectors based on the inter predictioninformation received from the entropy decoding unit 2010, and generatesa prediction block using the one or more reference pictures and the oneor more motion vectors.

The operation of the post-processing unit 2070 is the same of thepost-processing unit 1100 of FIG. 1.

The picture storing unit 2080 stores pictures which is post-processed bythe post-processing unit 2070.

FIG. 3 is a flow chart illustrating a deblocking filtering processaccording to the present invention.

The deblocking filtering process is performed by the post-processingunit 1100 of the moving picture encoding apparatus 1000 shown in FIG. 1and by the post-processing unit 2070 of the moving picture decodingapparatus 2000 shown in FIG. 2.

When it is determined that deblocking filtering is performed on a slice,the deblocking filtering process is applied to the slice. The movingpicture decoding apparatus uses a flag ‘diable_deblocking_filter_flag’received from a bit stream to determine whether the deblocking filteringis performed or not per slice.

The deblocking filtering is performed on each coding unit. The verticaledges are filtered first starting with the edge of the left-hand side ofthe coding unit toward the right-hand side of the coding unit. Then thehorizontal edges are filtered starting with the edge on the top of thecoding unit towards the bottom of the coding unit.

The deblocking filter is applied only to the prediction unit edges andthe transform unit edges. If the width or height of the prediction unitor the transform unit is smaller than 8-sample length, the deblockingfilter is applied only to the edges lying on 8×8 sample grid.

The boundary strength is determined on each 4-sample edge lying on 8×8sample grid (S110).

FIG. 4 is a conceptual diagram illustrating a method of determining theboundary strength according to the present invention.

As shown in FIG. 4, the boundary strength is determined on each 4-sampleedge lying 8×8 sample grid. Then, the boundary strength is determined onedges of 8×8 block using two consecutive boundary strength.

Accordingly, the computational complexity required to determine theboundary strength according to the present invention is reduced by 50%when compared with the HEVC under development. Also, the presentinvention reduces the memory capacity and bandwidth required todetermine the boundary strength by 50%. Therefore, the present inventionreduces the complexity of hardware and software without deterioration ofimage quality.

FIG. 5 is a conceptual diagram illustrating a 4-sample edge according tothe present invention. As shown in FIG. 5, the 4-sample edge is locatedbetween a P block containing sample p0 and a Q block containing sampleq0. The sample p0 corresponds to one of the samples p0 ₀˜p0 ₃, and thesample q0 corresponds one of the samples q0 ₀˜q0 ₃. The block P and Q isa prediction unit or a transform unit.

The boundary strength is determined as follows. The boundary strength isdetermined per 4-sample edge.

If the prediction unit containing the sample p0 or the prediction unitcontaining the sample q0 is intra-coded, the boundary strength of the4-sample edge is set equal to 2. The 4-sample edge is a prediction unitedge. That is, if the block P and block Q are inter-coded, the boundarystrength is set equal to 0 or 1.

If one or more following conditions are satisfied, the boundary strengthis set equal to 1.

1) The 4-sample edge is a transform unit edge, the transform unitcontaining the sample p0 or the transform unit containing the sample q0contains one or more non-zero transform coefficients.

2) The 4-sample edge is a prediction unit edge, the prediction unitcontaining the sample p0 and the prediction unit containing the sampleq0 are inter-coded, and the prediction unit containing the sample p0 orthe prediction unit containing the sample q0 have different referencepictures or a different number of motion vectors.

3) The prediction unit containing the sample p0 and the prediction unitcontaining the sample q0 are inter-coded, the prediction unit containingthe sample p0 and the prediction unit containing the sample q0 have onemotion vector, and the absolute difference between the horizontal orvertical component of the motion vectors is greater than or equal to apredetermined value (for example, 1 sample). The edge is not a part of ahorizontal boundary of LCU.

4) The prediction unit containing the sample p0 and the prediction unitcontaining the sample q0 are inter-coded, the prediction unit containingthe sample p0 and the prediction unit containing the sample q0 have twomotion vectors, the prediction unit containing the sample p0 and theprediction unit containing the sample q0 have at least one samereference picture, and the absolute difference between the horizontal orvertical component of two motion vectors corresponding to the samereference picture is greater than or equal to the predetermined value.The edge is not a part of a horizontal boundary of LCU.

As described above, if the 4-sample edge is not lying on the 8×8 samplegrid, the boundary strength is set equal to 0.

On the other hand, when the edge is a horizontal edge of LCU and aprediction unit containing the sample p0 is located above the horizontaledge of LCU, the motion information of the prediction unit containingthe sample p0 may be replaced with the motion information of a left orright neighboring prediction unit of the prediction unit containing thesample p0 based on the size and/or location of the prediction unitcontaining the sample p0.

Next, it is determined whether deblocking filtering is performed or noton the 4-sample edge (S120).

For 4-sample edge, deblocking filtering is performed if the followingtwo conditions are satisfied.

bS>0  1)

d<β  2)

The bS represents a boundary strength. The value of the variable 13 isdetermined based on a boundary quantization parameter QP_(B).

The variable d is defined as follows.

d=d _(p0) +dg ₀ +d _(p3) +d _(q3)  1)

d _(pk) =|p2_(k)−2·p1_(k) +p0_(k)| and d _(qk) =|q2_(k)−2·q1_(k)+q0_(k)|  2)

Next, if it is determined that deblocking filtering is applied to the4-sample edge, one deblocking filter is selected among a strong filterand a weak filter. But, if it is determined that deblocking filtering isnot applied to the 4-sample edge, the deblocking filtering process endsfor that edge. As shown in FIG. 5, a filter is selected for each4-sample edge.

If the following conditions are satisfied, the strong filter isselected.

d<(β>>2)  1)

|p3_(i) −p0_(i) |+|q3_(i) −q0_(i)|<(β>>3) for each i, i=0,3  2)

|p0_(i) −q0_(i)|<(5*t _(c)+1)>>1 for each i, i=0,3  3)

Or

d _(i)<(β>>1) for each i, i=0,3  1)

|p3_(i) −p0_(i) |+|q3_(i) −q0_(i)|<(β>>3) for each i, i=0,3  2)

|p0_(i) −q0_(i)|<(5*t _(c)+1)>>1 for each i, i=0,3  3)

Otherwise, the weak filter is selected. The value of the variable t_(c)is determined based on the boundary quantization parameter QP_(B).

Next, if the deblocking filter is selected, the edge is filtered usingthe deblocking filter (S140).

The strong filter is as follows.

p ₀′=(p ₂+2*p ₁+2*p ₀+2*q ₀ +q ₁+4)>>3)

p ₁′=(p ₂ +p ₁ +p ₀ +q ₀+2)>>2

p ₂′=(2*p ₃+3*p ₂ +p ₁ +p ₀ +q ₀+4)>>3

q ₀′=(p ₁+2*p ₀+2*q ₀+2*q ₁ +q ₂+4)>>3

q ₁ ^(′)=(p ₀ +q ₀ +q ₁ +q ₂+2)>>2

q ₂′=(p ₀ +q ₀ +q ₁+3*q ₂+2*q ₃+4)>>3

The weak filter is as follows.

Δ=Clip3(−t _(C) ,t _(C),Δ)

p ₀′=Clip1(p ₀+Δ)

q ₀′=Clip1(q ₀−Δ)

Δp=Clip3(−(t _(C)−1),t _(C)−1,(((p ₂ +p ₀+1)>>1)−p ₁+Δ)>>1)

p ₁′=Clip1(p ₁ +Δp)

Δq=Clip3(−(t _(C)>>1),t _(C)>>1,(((q ₂ +q ₀+1)>>1)−q ₁−Δ)>>1)

q ₁′=Clip1(q ₁ +Δq)

The variables β and t_(c) are determined by the boundary quantizationparameter QP_(B), and increases monotonically as the boundaryquantization parameter QP_(B) increases. The relation between theparameters β and t_(c), and the quantization parameter is defined as atable.

The boundary quantization parameter QP_(B) is an average of thequantization parameter QP_(P) of P block containing sample p0 and QP_(Q)of Q block containing sample q0. The average is a value rounded off. Ifat least one of P block and Q block is intra-coded, the parameter t_(c)increases by 0, 1 or 2 as the QP_(B) increases by 1.

Now, the sample adaptive offset process according to the presentinvention is described. The sample adaptive offset process is performedby the post-processing unit 1100 of the moving picture encodingapparatus 1000 shown in FIG. 1 and by the post-processing unit 2070 ofthe moving picture decoding apparatus 2000 shown in FIG. 2.

FIG. 6 is a conceptual diagram illustrating a method of dividing apicture into multiples areas according to the present invention. A SAOtype is defined per area.

As shown in FIG. 6, the areas are generated by dividing a picture in aquadtree structure. The area may be an LCU. There are three kinds of SAOtypes. If the SAO type is the first type (OFF), the SAO process is notperformed on the corresponding area. If SAO type indicates band offset(BO), a band offset is added to each sample within the area. If SAO typeindicates edge offset (EO), an edge offset determined by an edge indexis added to each sample within the area.

FIG. 7 is a conceptual diagram illustrating edge types according to thepresent invention.

As shown in FIG. 7, there exist four edge types in the edge offset. Theedge type is determined by positions of neighboring samples used toderive an edge index. The first edge type indicates 1D 0-degree edgetype, the second edge type indicates 1D 90-degree edge type, the thirdedge type indicates 1D 135-degree edge type, and the fourth edge typeindicates 1D 90-degree edge type. The sample C represents a currentsample and the two shaded samples represent two neighboring samplesdetermined by the edge type.

The sample adaptive offset process is performed as follows when thesample adaptive offset type indicates one of edge offset types accordingto the present invention.

First, an edge index is derived using the differences between a currentsample and two neighboring samples. The two neighboring samples aredetermined by the edge offset type of a current area. The edge index isderived per sample within the current area. The edge index is derived asfollows.

edgeIdx=2+sign3(recPicture(x)−recPicture(x−1))+sign3(recPicture(x)−recPicture(x+1))

The function sign3(y) is equal to 1 if the y is larger than 0, thefunction sign3(y) is equal to −1 if the y is smaller than 0, and thefunction sign3(y) is equal to 0 if the y is equal to 0.

The variable recPicture(x) represents the current sample value, thevariables recPicture(x−1) and recPicture(x+1) represent the twoneighboring sample values. The two neighboring samples are determined bythe edge offset type of the current area.

FIG. 8 is a conceptual diagram illustrating edge indexes according tothe present invention. In FIG. 8, the horizontal axis represents sampleposition and the vertical axis represents sample value.

As shown in FIG. 8, the edge index is set to 0 if both of the twoneighboring sample values are larger than the current sample value, theedge index is set to 1 if one of the two neighboring sample values islarger than the current sample and the other is equal to the currentsample value, the edge index is set to 2 if one of the two neighboringsample values is larger than the current sample and the other is smallerthan the current sample value, the edge index is set to 3 if one of thetwo neighboring sample values is smaller than the current sample and theother is equal to the current sample value, and the edge index is set to4 if both of the two neighboring sample values are smaller than thecurrent sample. The edge index is also set to 2 if both of the twoneighboring sample values are equal to the current sample.

Meanwhile, when one of the two neighboring samples belongs to anotherLCU, the edge offset may be not applied to the current sample or anotherneighboring sample within the current LCU is used instead of theneighboring sample belonging to the another LCU.

Next, an edge offset is added to the current sample as follows.

recSaoPicture(x)=recPicture(x)+Edge_Offset[edgeIdx]

The edge offset is determined based on the edge index. In the movingpicture decoding apparatus 2000, the edge offset is obtained from a bitstream transmitted from the moving picture encoding apparatus 1000. Themoving picture encoding apparatus 1000 may transmits 4 or 5 edgeoffsets. If 4 edge offsets are transmitted, the 4 edges offsetscorrespond to the edge indexes 0, 1, 3, 4 respectively, the edge offsetis considered as 0.

The edge offset may be a positive value or a negative value. Thequantity of bits required to transmit the 4 edges offsets increases asthe area is larger. A method of reducing the quantity of bits accordingto the present invention is as follows.

First Embodiment

A positive offset is applied to the edge index 0 and a negative offsetis applied to the edge index 4. That is, only the absolute values of thetwo edge offsets are transmitted to reduce the quantity of bits. Foredge indexes 1 and 3, the absolute value and sign of the edge offset aretransmitted.

Second Embodiment

A positive offset is applied to the edge indexes 0 and 1 and a negativeoffset is applied to the edge indexes 3 and 4. That is, only theabsolute values of the four edge offsets are transmitted to reduce thequantity of bits.

Furthermore, the offset is not added to the current sample if thedifference between the current sample and a neighboring sample is largerthan a threshold. For example, if the absolute value of the differencebetween the current sample and a neighboring sample is larger than thethreshold, the offset value is set to 0. Otherwise, the negative offsetor the positive offset is used.

While the invention has been shown and described with reference tocertain exemplary embodiments thereof, it will be understood by thoseskilled in the art that various changes in form and details may be madetherein without departing from the spirit and scope of the invention asdefined by the appended claims.

What is claimed is:
 1. A method of post-processing a reconstructedimage, the method comprising determining a boundary strength for each4-sample edge which is a prediction edge or a transform edge and lies on8×8 sample grid; determining whether deblocking filtering is applied onthe 4-sample edge or not using the boundary strength and a boundaryquantization parameter; filtering the 4-sample edge if the deblockingfiltering is applied on the 4-sample edge; and applying an edge offsetif a sample adaptive offset (SAO) type indicates an edge offset, whereinthe step of applying an edge offset comprises the sub-steps of:generating an edge index of a current sample; and generating an edgeoffset corresponding to the edge index to the current sample, whereinthe edge index is generated using the following equation,edgeIdx=2+sign3(recPicture(x)−recPicture(x−1))+sign3(recPicture(x)−recPicture(x+1)),wherein the function sign3(y) is equal to 1 if the y is larger than 0,the function sign3(y) is equal to −1 if the y is smaller than 0, and thefunction sign3(y) is equal to 0 if the y is equal to 0, wherein thevariable recPicture(x) represents the current sample value, and thevariables recPicture(x−1) and recPicture(x+1) represent the twoneighboring sample values, wherein the boundary quantization parameteris an average of a quantization parameter of P block containing samplep0 and a quantization parameter of Q block containing sample q0, thequantization parameter of the P block is generated by using aquantization parameter predictor and a differential quantizationparameter of the P block, and if two or more quantization parameters areavailable among a left quantization parameter, an above quantizationparameter and a previous quantization parameter of the P block, thequantization parameter predictor of the P block is generated using twoavailable quantization parameters which are determined according to apredetermined order, and wherein the 4-sample edge is filtered using afilter which is selected between a strong filter and a weak filter. 2.The method of claim 1, wherein the two neighboring samples aredetermined by an edge offset type of a current area.
 3. The method ofclaim 1, wherein the edge offset is set as negative or positive based onthe edge index.
 4. The method of claim 3, wherein the edge offset is setas positive if the edge index is equal to 0 or
 1. 5. The method of claim3, wherein the edge offset is set as negative if the edge index is equalto 3 or
 4. 6. The method of claim 1, wherein the edge offset is set to 0if the edge index is equal to
 2. 7. The method of claim 1, wherein ifone of the two neighboring samples belongs to another LCU, the edgeoffset is not applied to the current sample.
 8. The method of claim 1,wherein if one of the two neighboring samples belongs to another LCU,the neighboring sample belonging to another LCU is replaced with anothersample within LCU.
 9. The method of claim 1, wherein if only onequantization parameter is available among the left quantizationparameter, the above quantization parameter and the previousquantization parameter of the P block, the available quantizationparameter is set as the quantization parameter predictor of the P block.